Yu Luo, Ke Gao, Miller Fawaz, Bo Wu, Yi Zhong, Yong Zhou, Ewart Mark Haacke, Yongming Dai, Shiyuan Liu
BACKGROUND: Efficiently and accurately detecting cerebral microbleeds (CMBs) is crucial for diagnosing dementia, stroke, and traumatic brain injury. Manual CMB detection, however, is time-consuming and error-prone. This study evaluates a novel artificial intelligence (AI) software designed for the automated detection of CMBs using susceptibility weighted imaging (SWI). METHODS: The SWI data from 265 patients, 206 of whom had a history of stroke and others of whom presented a variety of other medical histories, including hypertension, diabetes, hyperlipidemia, cerebral hemorrhage, intracerebral vascular malformations, tumors, and inflammation, collected between January 2015 and December 2018, were analyzed...
March 15, 2024: Quantitative Imaging in Medicine and Surgery